Neurotechnology, a provider of high-precision biometric identification technologies, recently released its new surveillance SDK for biometric facial identification, using still images and live video streams from high-resolution surveillance cameras. The technology assures system performance and reliability with live-face detection, simultaneous multiple-face recognition and fast face matching in one-to-one and one-to-many modes.

Unlike other facial-recognition systems in the market today that require a person to be actively looking into a camera for recognition, Neurotechnology's SDK is intended for real-time identification of faces regardless of the direction in which a person is looking. Live-face detection prevents cheating by placing a photo in front of a camera, a problem often faced by other biometric identification tools.

When a camera is mounted near an entrance to track when and who enters or exits a premise, the SDK enables fast, automatic counting and recognition of individuals as they pass through.

"The ability to use surveillance cameras to identify passive users provides a range of new applications for facial identification such as law enforcement for public surveillance, airport security, shops and other commercial uses," said Dr. Algimantas Malickas, CEO of Neurotechnology.

Matching against Internal DatabaseNeurotechnology's SDK uses algorithms that implement face localization, enrollment and matching. It processes facial images in video streams and then matches them against an internal database such as a watch list of crime suspects or a list of authorized and unauthorized personnel.

Faces that are recognized are immediately reported to the system and security personnel alerted. Once a face is detected, it is tracked in all successive frames of video until it disappears entirely from the camera view. The SDK also allows for automatic enrollment of faces from a video source and new biometric facial templates can be updated to the database or watch list at any time.

Enabling real-time face detection, extraction and matching by providing embedded parallelization of the SDK's functions improves performance on multicore, multiprocessor systems with up to eight logical processors. This means that the SDK can work with a wide variety of high-resolution cameras. Furthermore, for easier integration and adoption, the SDK supports a range of programming languages.

The SDK enables the development of fast, reliable, cost-effective, biometric facial-identification systems for both Windows and Linux platforms, revolutionizing the efficiency and practice of law enforcement as well as commercial security.